Citations are references to published or unpublished documents or sources in science, law, or other fields to identify or refer to documents, articles, books, legislation, court opinions, patents, legal filings, etc.
There are various citation index products available today. However, the citation index networks analyzed by these products are limited to explicit citation linkages between documents—cited and citing. Certain citation linkages are clear, e.g. Case A cites Case B which cites Case C. What is less clear, but of possible equal importance, is where Case A somehow impacts Case C but the impact is latent and only visible through an investigation of the facets discussed that are common between A and C. In such situations, the authority of Case C may have been subject to an influencing judgment that increases or decreases the authority of Case A. Current index products do not show this connection. Today, users are required to perform their own lengthy research to identify whether or not factual and legal issues have been damaged by an implicit citation linkage that exists outside of the explicit citing cited change of documents.
Generally, there is a lack of a comprehensive and systematic identification and linking of implicit citations through a multi-generational, multi-node citation network.
Accordingly, there exists a need for methods and systems that expand the citation network analysis beyond explicit references. Such methods and systems would improve research efficiency through citation analysis by including both implicit references as well as deeper analysis of citation network indicators of significance.